Article
| December 1, 2014

By Anne Stroup, Vice President of Strategy, Alliance Life Sciences Consulting Group

As today’s information-craving customers force the life sciences industry to change their sales and marketing model, innovative customer engagement models are sought as a revenue-generation lever. Message reach and frequency no longer equate to sales. Now it’s about building and sustaining customer loyalty by delivering value. Top-line and market share growth are perpetuated by the quality of customer engagements.

Moving from brand message to customer needs requires sales, marketing and technology teams to revise their strategies. To implement this new communication approach, life sciences companies will face some key challenges. Understanding these core challenges is the first step toward customer communication transformation, a journey that leads to growth, cost reductions and enhanced technology value.

Technology to deliver deeper customer understanding

Through a deeper customer understanding, actual needs are identified and a brand can deliver value. The exploration of causal relationships between traditional and big data sources more fully identifies customer needs, behavior triggers, promotional receptivity and their financial value potential. The main challenge is that expended data sources and agile analytic environment are not complementary to many legacy systems. And without the application of new data methods, in-depth customer view isn’t achievable. However, evolved analytic ecosystems, experienced data scientists and engagement strategists can create small wins and build the transformed environment.

Expertise to translate customer insights into new engagement strategies

True customer engagement is like a dialogue that strategically layers personal and multi-channel interactions, offering content based on customer needs, which is then delivered when and how customers choose to receive it. Continuously turning each customer touch point into a relevant brand experience is a complex proposition. Customer engagement requires systems to manage the rules associated with each interaction.

Building a systematic communications plan based on the customer journey becomes a key challenge. Highly detailed journey maps translate insights into the construct of every customer touch point. This lays the foundation for push-and-pull content development, engagement business rules and channel selection. Adding engagement marketing expertise complements a marketing team.

Customer engagement requires systems to manage the rules associated with each interaction. Pre-planned content and channel decisions drive communications and enable near real-time responses. All of which are designed to align customer-value potential with promotional investment. Sales and marketing system integration coupled with rapid processing capabilities, and pre-planned communication decisions are imperative to the customer-centric model.

Having the ability to explore massive volumes of data, uncover new insights and rapidly move insights to action is a competitive differentiator. Knowledge-based decisions allow companies to maximize brand opportunities, align resource utilization with promotional lifecycle and customer value, and gain process efficiencies throughout the commercial operation. The shift to the customer-centric model necessitates alignment of technology strategies, media and other vendor agreements.

Each technology change brings the opportunity to generate value. Evolving the infrastructure to manage multi-structured data sources, real-time decision making, and shared data repositories -- while assuring data quality and flexible system interface -- will require commercial transformation. Partnering to assess the current environment and plan the path forward adds new thinking and skills to this evolutionary process. Gaining value is paramount. Creating an analytic ecosystem offers an interim step between infrastructure readiness and insight value. A cloud-based environment enables the advanced modeling techniques needed to build effectiveness and efficiencies.

In order for data-driven decision to work, data must matter to all employees. The diligence to collect, standardize, and share data from every customer touch point feeds the system and permits a continuous learning environment.

Preparing the team to embrace an innovative customer engagement model will deliver the improved revenue, reduced costs and operational efficiencies that come when transforming how to communicate with customers. It is a cultural evolution that requires consistent nurturing and a dedicated team to lead a carefully orchestrated process.

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